• Darshna Parmar
• Rasika Thakare

There are many online music services are available with huge amount of musical tracks. So people are getting more time for searching the music according to their taste. Recommendation is the way to solve that problem. Recommendation can be better if music feature selection is done in a proper way. Music has Editorial property e.g. album, artist etc. and subjective property e.g. acousticness, loudness etc. As per research found that music is a subjective. It is better to use subjective features for recommendation because different people may have different kind of perception for same music. Here, subjective features of music are analyzed and music genre category is identified. This is used for base of recommendation method. This paper contains technique to cluster music based on feature attribute value using Spotify API and K mean clustering Algorithm is used to match music attribute value with cluster centroid value. The result is used to predict the music based on different attribute value.

There are many online music services are available with huge amount of musical tracks. So people are getting more time for searching the music according to their taste. Recommendation is the way to solve that problem. Recommendation can be better if music feature selection is done in a proper way. Music has Editorial property e.g. album, artist etc. and subjective property e.g. acousticness, loudness etc. As per research found that music is a subjective. It is better to use subjective features for recommendation because different people may have different kind of perception for same music. Here, subjective features of music are analyzed and music genre category is identified. This is used for base of recommendation method. This paper contains technique to cluster music based on feature attribute value using Spotify API and K mean clustering Algorithm is used to match music attribute value with cluster centroid value. The result is used to predict the music based on different attribute value.

"Music Prediction Using Musical Subjective Features", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.468-471, May-2019, Available :http://www.jetir.org/papers/JETIR1905572.pdf

"Music Prediction Using Musical Subjective Features", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp468-471, May-2019, Available at : http://www.jetir.org/papers/JETIR1905572.pdf